112 resultados para Morbidity and mortality

em Queensland University of Technology - ePrints Archive


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Background There are minimal reports of seasonal variations in chronic heart failure (CHF)-related morbidity and mortality beyond the northern hemisphere. Aims and methods We examined potential seasonal variations with respect to morbidity and all-cause mortality over more than a decade in a cohort of 2961 patients with CHF from a tertiary referral hospital in South Australia subject to mild winters and hot summers. Results Seasonal variation across all event-types was observed. CHF-related morbidity peaked in winter (July) and was lowest in summer (February): 70 (95% CI: 65 to 76) vs. 33 (95% CI: 30 to 37) admissions/1000 at risk (p<0.005). All-cause admissions (113 (95% CI: 107 to 120) vs. 73 (95% CI 68 to 79) admissions/1000 at risk, p<0.001) and concurrent respiratory disease (21% vs. 12%,p<0.001) were consistently higher in winter. 2010 patients died, mortality was highest in August relative to February: 23 (95% CI: 20 to 27) vs. 12 (95% CI: 10 to 15) deaths per 1000 at risk, p<0.001. Those aged 75 years or older were most at risk of seasonal variations in morbidity and mortality. Conclusion Seasonal variations in CHF-related morbidity and mortality occur in the hot climate of South Australia, suggesting that relative (rather than absolute) changes in temperature drive this global phenomenon.

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Catheter associated urinary tract infections (CAUTI) are a worldwide problem that may lead to increased patient morbidity, cost and mortality.1e3 The literature is divided on whether there are real effects from CAUTI on length of stay or mortality. Platt4 found the costs and mortality risks to be largeyetGraves et al found the opposite.5 A reviewof the published estimates of the extra length of stay showed results between zero and 30 days.6 The differences in estimates may have been caused by the different epidemiological methods applied. Accurately estimating the effects of CAUTI is difficult because it is a time-dependent exposure. This means that standard statistical techniques, such asmatched case-control studies, tend to overestimate the increased hospital stay and mortality risk due to infection. The aim of the study was to estimate excess length of stay andmortality in an intensive care unit (ICU) due to a CAUTI, using a statistical model that accounts for the timing of infection. Data collected from ICU units in lower and middle income countries were used for this analysis.7,8 There has been little research for these settings, hence the need for this paper.

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Background The Global Burden of Diseases (GBD), Injuries, and Risk Factors study used the disability-adjusted life year (DALY) to quantify the burden of diseases, injuries, and risk factors. This paper provides an overview of injury estimates from the 2013 update of GBD, with detailed information on incidence, mortality, DALYs and rates of change from 1990 to 2013 for 26 causes of injury, globally, by region and by country. Methods Injury mortality was estimated using the extensive GBD mortality database, corrections for ill-defined cause of death and the cause of death ensemble modelling tool. Morbidity estimation was based on inpatient and outpatient data sets, 26 cause-of-injury and 47 nature-of-injury categories, and seven follow-up studies with patient-reported long-term outcome measures. Results In 2013, 973 million (uncertainty interval (UI) 942 to 993) people sustained injuries that warranted some type of healthcare and 4.8 million (UI 4.5 to 5.1) people died from injuries. Between 1990 and 2013 the global age-standardised injury DALY rate decreased by 31% (UI 26% to 35%). The rate of decline in DALY rates was significant for 22 cause-of-injury categories, including all the major injuries. Conclusions Injuries continue to be an important cause of morbidity and mortality in the developed and developing world. The decline in rates for almost all injuries is so prominent that it warrants a general statement that the world is becoming a safer place to live in. However, the patterns vary widely by cause, age, sex, region and time and there are still large improvements that need to be made.

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Background Primary prevention of childhood overweight is an international priority. In Australia 20-25% of 2-8 year olds are already overweight. These children are at substantially increased the risk of becoming overweight adults, with attendant increased risk of morbidity and mortality. Early feeding practices determine infant exposure to food (type, amount, frequency) and include responses (eg coercion) to infant feeding behaviour (eg. food refusal). There is correlational evidence linking parenting style and early feeding practices to child eating behaviour and weight status. A focus on early feeding is consistent with the national focus on early childhood as the foundation for life-long health and well being. The NOURISH trial aims to implement and evaluate a community-based intervention to promote early feeding practices that will foster healthy food preferences and intake and preserve the innate capacity to self-regulate food intake in young children. Methods/Design This randomised controlled trial (RCT) aims to recruit 820 first-time mothers and their healthy term infants. A consecutive sample of eligible mothers will be approached postnatally at major maternity hospitals in Brisbane and Adelaide. Initial consent will be for re-contact for full enrolment when the infants are 4-7 months old. Individual mother- infant dyads will be randomised to usual care or the intervention. The intervention will provide anticipatory guidance via two modules of six fortnightly parent education and peer support group sessions, each followed by six months of regular maintenance contact. The modules will commence when the infants are aged 4-7 and 13-16 months to coincide with establishment of solid feeding, and autonomy and independence, respectively. Outcome measures will be assessed at baseline, with follow up at nine and 18 months. These will include infant intake (type and amount of foods), food preferences, feeding behaviour and growth and self-reported maternal feeding practices and parenting practices and efficacy. Covariates will include sociodemographics, infant feeding mode and temperament, maternal weight status and weight concern and child care exposure. Discussion Despite the strong rationale to focus on parents’ early feeding practices as a key determinant of child food preferences, intake and self-regulatory capacity, prospective longitudinal and intervention studies are rare. This trial will be amongst to provide Level II evidence regarding the impact of an intervention (commencing prior to age 12 months) on children’s eating patterns and behaviours. Trial Registration: ACTRN12608000056392

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Background: Poor appetite is a marker of morbidity and mortality in hemodialysis patients, making it an important area for research. Visual analog scales (VAS) can capture a range of subjective sensations related to appetite (such as hunger, desire to eat or fullness), but have not been commonly used to measure appetite in dialysis patients. The aim of this study was to explore the association between retrospective ratings of appetite using VAS and a range of clinical variables as well as biomarkers of appetite in hemodialysis patients.----- Methods: 28 hemodialysis patients (mean age 61±17y, 50% male, median dialysis vintage 19.5(4-101) months) rated their appetite using VAS for hunger, fullness and desire to eat and a 5-point categorical scale measuring general appetite. Blood levels of the appetite peptides leptin, ghrelin and peptide YY were also measured.----- Results: Hunger ratings measured by VAS were significantly (p<0.05) correlated with a range of clinical, nutritional and inflammatory markers: age (r=-0.376), co-morbidities, (r=-0.380) PG-SGA score (r=-0.451), weight (r=-0.375), fat-free mass (r=-0.435), C-Reactive Protein (CRP) (r=-0.383) and Intercellular adhesion molecule (sICAM-1) (r=-0.387). There was a consistent relationship between VAS and appetite on a 5-point categorical scale for questions of hunger, and a similar trend for desire to eat, but not for fullness. Neither method of measuring subjective appetite correlated with appetite peptides.----- Conclusions: Retrospective ratings of hunger on a VAS are associated with a range of clinical variables and further studies are warranted to support their use as a method of measuring appetite in dialysis patients.

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Dehydration has been associated with increased morbidity and mortality. Dehydration risk increases with advancing age, and will progressively become an issue as the aging population increases. Worldwide, those aged 60 years and over are the fastest growing segment of the population. The study aimed to develop a clinically practical means to identify dehydration amongst older people in the clinical care setting. Older people aged 60 years or over admitted to the Geriatric and Rehabilitation Unit (GARU) of two tertiary teaching hospitals were eligible for participation in the study. Ninety potential screening questions and 38 clinical parameters were initially tested on a single sample (n=33) with the most promising 11 parameters selected to undergo further testing in an independent group (n=86). Of the almost 130 variables explored, tongue dryness was most strongly associated with poor hydration status, demonstrating 64% sensitivity and 62% specificity within the study participants. The result was not confounded by age, gender or body mass index. With minimal training, inter-rater repeatability was over 90%. This study identified tongue dryness as a potentially practical tool to identify dehydration risk amongst older people in the clinical care setting. Further studies to validate the potential screen in larger and varied populations of older people are required

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Introduction: The core business of public health is to protect and promote health in the population. Public health planning is the means to maximise these aspirations. Health professionals develop plans to address contemporary health priorities as the evidence about changing patterns of mortality and morbidity is presented. Officials are also alert to international trends in patterns of disease that have the potential to affect the health of Australians. Integrated planning and preparation is currently underway involving all emergency health services, hospitals and population health units to ensure Australia's quick and efficient response to any major infectious disease outbreak, such as avian influenza (bird flu). Public health planning for the preparations for the Sydney Olympics and Paralympic Games in 2000 took almost three years. ‘Its major components included increased surveillance of communicable disease; presentations to sentinel emergency departments; medical encounters at Olympic venues; cruise ship surveillance; environmental and food safety inspections; bioterrorism surveillance and global epidemic intelligence’ (Jorm et al 2003, 102). In other words, the public health plan was developed to ensure food safety, hospital capacity, safe crowd control, protection against infectious diseases, and an integrated emergency and disaster plan. We have national and state plans for vaccinating children against infectious diseases in childhood; plans to promote dental health for children in schools; and screening programs for cervical, breast and prostate cancer. An effective public health response to a change in the distribution of morbidity and mortality requires planning. All levels of government plan for the public’s health. Local governments (councils) ensure healthy local environments to protect the public’s health. They plan parks for recreation, construct traffic-calming devices near schools to prevent childhood accidents, build shade structures and walking paths, and even embed drafts/chess squares in tables for people to sit and play. Environmental Health officers ensure food safety in restaurants and measure water quality. These public health measures attempt to promote the quality of life of residents. Australian and state governments produce plans that protect and promote health through various policy and program initiatives and innovations. To be effective, program plans need to be evaluated. However, building an integrated evaluation plan into a program plan is often forgotten, as planning and evaluation are seen as two distinct entities. Consequently, it is virtually impossible to measure, with any confidence, the extent to which a program has achieved its goals and objectives. This chapter introduces you to the concepts of public health program planning and evaluation. Case studies and reflection questions are presented to illustrate key points. As various authors use different terminology to describe the same concepts/actions of planning and evaluation, the glossary at the back of this book will help you to clarify the terms used in this chapter.

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Globally, the main contributors to morbidity and mortality are chronic diseases, including cardiovascular disease and diabetes. Chronic diseases are costly and partially avoidable, with around sixty percent of deaths and nearly fifty percent of the global disease burden attributable to these conditions. By 2020, chronic illnesses will likely be the leading cause of disability worldwide. Existing health care systems, both national and international, that focus on acute episodic health conditions, cannot address the worldwide transition to chronic illness; nor are they appropriate for the ongoing care and management of those already afflicted with chronic diseases. International and Australian strategic planning documents articulate similar elements to manage chronic disease; including the need for aligning sectoral policies for health, forming partnerships and engaging communities in decision-making. The Australian National Chronic Disease Strategy focuses on four core areas for managing chronic disease; prevention across the continuum, early detection and treatment, integrated and coordinated care, and self-management. Such a comprehensive approach incorporates the entire population continuum, from the ‘healthy’, to those with risk factors, through to people suffering from chronic conditions and their sequelae. This chapter examines comprehensive approach to the prevention, management and care of the population with non-communicable, chronic diseases and communicable diseases. It analyses models of care in the context of need, service delivery options and the potential to prevent or manage early intervention for chronic and communicable diseases. Approaches to chronic diseases require integrated approaches that incorporate interventions targeted at both individuals and populations, and emphasise the shared risk factors of different conditions. Communicable diseases are a common and significant contributor to ill health throughout the world. In many countries, this impact has been minimised by the combined efforts of preventative health measures and improved treatment of infectious diseases. However in underdeveloped nations, communicable diseases continue to contribute significantly to the burden of disease. The aim of this chapter is to outline the impact that chronic and communicable diseases have on the health of the community, the public health strategies that are used to reduce the burden of those diseases and the old and emerging risks to public health from infectious diseases.

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In this thesis, the relationship between air pollution and human health has been investigated utilising Geographic Information System (GIS) as an analysis tool. The research focused on how vehicular air pollution affects human health. The main objective of this study was to analyse the spatial variability of pollutants, taking Brisbane City in Australia as a case study, by the identification of the areas of high concentration of air pollutants and their relationship with the numbers of death caused by air pollutants. A correlation test was performed to establish the relationship between air pollution, number of deaths from respiratory disease, and total distance travelled by road vehicles in Brisbane. GIS was utilized to investigate the spatial distribution of the air pollutants. The main finding of this research is the comparison between spatial and non-spatial analysis approaches, which indicated that correlation analysis and simple buffer analysis of GIS using the average levels of air pollutants from a single monitoring station or by group of few monitoring stations is a relatively simple method for assessing the health effects of air pollution. There was a significant positive correlation between variable under consideration, and the research shows a decreasing trend of concentration of nitrogen dioxide at the Eagle Farm and Springwood sites and an increasing trend at CBD site. Statistical analysis shows that there exists a positive relationship between the level of emission and number of deaths, though the impact is not uniform as certain sections of the population are more vulnerable to exposure. Further statistical tests found that the elderly people of over 75 years age and children between 0-15 years of age are the more vulnerable people exposed to air pollution. A non-spatial approach alone may be insufficient for an appropriate evaluation of the impact of air pollutant variables and their inter-relationships. It is important to evaluate the spatial features of air pollutants before modeling the air pollution-health relationships.

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The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

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Poor patient compliance with peritoneal dialysis (PD) has significant adverse effects on morbidity and mortality rates in individuals with chronic kidney disease (CKD). It also adds to the resource burdens of healthcare services and providers. This paper explores the notion of PD compliance in patients with CKD with reference to the relevant published literature. The analysis of the literature reveals that ‘PD compliance’ is a complex and challenging construct for both patients and health professionals. There is no universal definition of compliance that is widely adopted in practice and research, and therefore a lack of consensus on how to determine ‘compliant’ patient outcomes. There are also multiple and interconnected determinants of PD compliance that are context-bound, which healthcare professionals must be aware of, and which makes producing consensus of measuring PD compliance difficult. The complexity of the interventions required to produce even a modest improvement in PD compliance, which are described in this paper, are significant. Compliance with PD and other treatments for CKD is a multidimensional, context-bound concept, that to date has tended to efface the role and needs of the renal patient. We conclude the paper with the implications for contemporary practice.

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Diabetic peripheral neuropathy (DPN) is one of the most debilitating complications of diabetes. DPN is a major cause of foot ulceration and lower limb amputation. Early diagnosis and management is a key factor in reducing morbidity and mortality. Current techniques for clinical assessment of DPN are relatively insensitive for detecting early disease or involve invasive procedures such as skin biopsies. There is a need for less painful, non-invasive and safe evaluation methods. Eye care professionals already play an important role in the management of diabetic retinopathy; however recent studies have indicated that the eye may also be an important site for the diagnosis and monitoring of neuropathy. Corneal nerve morphology has been shown to be a promising marker of diabetic neuropathy occurring elsewhere in the body, and emerging evidence tentatively suggests that retinal anatomical markers and a range of functional visual indicators could similarly provide useful information regarding neural damage in diabetes – although this line of research is, as yet, less well established. This review outlines the growing body of evidence supporting a potential diagnostic role for retinal structure and visual functional markers in the diagnosis and monitoring of peripheral neuropathy in diabetes.

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Background: A number of studies have examined the relationship between high ambient temperature and mortality. Recently, concern has arisen about whether this relationship is modified by socio-demographic factors. However, data for this type of study is relatively scarce in subtropical/tropical regions where people are well accustomed to warm temperatures. Objective: To investigate whether the relationship between daily mean temperature and daily all-cause mortality is modified by age, gender and socio-economic status (SES) in Brisbane, Australia. Methods: We obtained daily mean temperature and all-cause mortality data for Brisbane, Australia during 1996–2004. A generalised additive model was fitted to assess the percentage increase in all deaths with every one degree increment above the threshold temperature. Different age, gender and SES groups were included in the model as categorical variables and their modification effects were estimated separately. Results: A total of 53,316 non-external deaths were included during the study period. There was a clear increasing trend in the harmful effect of high temperature on mortality with age. The effect estimate among women was more than 20 times that among men. We did not find an SES effect on the percent increase associated with temperature. Conclusions: The effects of high temperature on all deaths were modified by age and gender but not by SES in Brisbane, Australia.

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Background: Ambulance ramping within the Emergency Department (ED) is a common problem both internationally and in Australia. Previous research has focused on various issues associated with ambulance ramping such as access block, ED overcrowding and ambulance bypass. However, limited research has been conducted on ambulance ramping and its effects on patient outcomes. ----- ----- Methods: A case-control design was used to describe, compare and predict patient outcomes of 619 ramped (cases) vs. 1238 non-ramped (control) patients arriving to one ED via ambulance from 1 June 2007 to 31 August 2007. Cases and controls were matched (on a 1:2 basis) on age, gender and presenting problem. Outcome measures included ED length of stay and in-hospital mortality. ----- ----- Results: The median ramp time for all 1857 patients was 11 (IQR 6—21) min. Compared to nonramped patients, ramped patients had significantly longer wait time to be triaged (10 min vs. 4 min). Ramped patients also comprised significantly higher proportions of those access blocked (43% vs. 34%). No significant difference in the proportion of in-hospital deaths was identified (2%vs. 3%). Multivariate analysis revealed that the likelihood of having an ED length of stay greater than eight hours was 34% higher among patients who were ramped (OR 1.34, 95% CI 1.06—1.70, p = 0.014). In relation to in-hospital mortality age was the only significant independent predictor of mortality (p < 0.0001). ----- ----- Conclusion: Ambulance ramping is one factor that contributes to prolonged ED length of stay and adds additional strain on ED service provision. The potential for adverse patient outcomes that may occur as a result of ramping warrants close attention by health care service providers.